Evidence map›Paper›PMID 35335452›Full record

ArticlePolymers2022

Starch/Polyaniline Biopolymer Film as Potential Intelligent Food Packaging with Colourimetric Ammonia Sensor.

Min-Rui Chia, Ishak Ahmad, Sook-Wai Phang

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 42 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Min-Rui ChiaPolymer Research Centre (PORCE), Department of Chemical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.ORCID 0000-0001-6633-3244
Ishak AhmadPolymer Research Centre (PORCE), Department of Chemical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
Sook-Wai PhangDepartment of Physical Science, Faculty of Applied Sciences, Tunku Abdul Rahman University College, Setapak, Kuala Lumpur 53300, Malaysia.
National University of Malaysia · MYTunku Abdul Rahman University of Management and Technology · MY

Funding

Ministry of Higher Education MYPAIR/1/2020/TK05/UKM//1National University of Malaysia GUP-2020-048
6 · The paper itself

Abstract

The use of petroleum-based plastics in food packaging leads to various environmental impacts, while spoilage of food and misinterpretation of food-date labelling account for food insecurity; therefore, a biopolymer capable of indicating food edibility is prepared to resolve these issues. In this research, starch/polyaniline (starch/PANI) biopolymer film was synthesised and investigated as an ammonia sensor for potential application as intelligent food packaging. FT-IR and XRD were used to confirm the composition of the biopolymer films, while UV-Vis spectrometry was applied to identify the oxidation state of PANI in emeraldine form. PANI was successfully incorporated into the starch matrix, leading to better thermal stability (TGA) but decreasing the crystallinity of the matrix (DSC). The performance of the polymer-film sensor was determined through ammonia-vapour sensitivity analysis. An obvious colour change from green to blue of starch/PANI films was observed upon exposure to the ammonia vapour. Starch/PANI 0.4% is the optimum composition, having the best sensor performance with good linearity (R

Indexed as

ammonia sensorbiopolymer filmintelligent food packagingpolyanilinestarch

Identifiers

PMID35335452
PMCPMC8955865
OpenAlexW4220824855

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.